Non-parametric Panel Data Models with Interactive Fixed Effects
Review of Economic Studies, 2018, vol. 85, issue 3, 1824-1851
This article studies non-parametric panel data models with multidimensional, unobserved individual effects when the number of time periods is fixed. I focus on models where the unobservables have a factor structure and enter an unknown structural function non-additively. The setup allows the individual effects to impact outcomes differently in different time periods and it allows for heterogeneous marginal effects. I provide sufficient conditions for point identification of all parameters of the model. Furthermore, I present a non-parametric sieve maximum likelihood estimator as well as flexible semiparametric and parametric estimators. Monte Carlo experiments demonstrate that the estimators perform well in finite samples. Finally, in an empirical application, I use these estimators to investigate the relationship between teaching practice and student achievement. The results differ considerably from those obtained with commonly used panel data methods.
Keywords: Panel data; Multidimensional individual effects; Factor model; Non-parametric identification (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:oup:restud:v:85:y:2018:i:3:p:1824-1851.
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